A Data Fusion Approach to Mobile Location Estimation based on Ellipse Propagation Model within a Cellular Radio Network

Mobile location estimation is drawing considerable attention in the field of wireless communications. In this paper, we present a new estimator which considers all the information to reduce the effect of signal fluctuation and fading-the statistical estimation. The Statistical Estimation is derived from the information of the received signal strengths (RSSs) and the locations of their corresponding base stations (BSs) and then estimates the location of the mobile station (MS). The statistical estimation uses all the information to provide the estimation of the location of the MS, which can provide an accurate estimation and reduce the effect of signal fluctuation and fading. It is a data fusion method to handle the signal fluctuation and fading problem. We test our approach with real data collected from Hong Kong. Experimental results show that our approach outperforms other existing location estimation algorithms among different kinds of terrains. The improvements based on the geometric algorithm with EPM and the iterative algorithm with EPM are 18.87% and 4.46%, respectively.